Energy Efficiency in Rate-Splitting Multiple Access with Mixed Criticality

TL;DR

This paper proposes a low-complexity rate-splitting algorithm for 6G C-RANs that optimizes energy efficiency and QoS for users with mixed criticality, demonstrating improved EE over existing schemes.

Contribution

It introduces a novel fractional programming-based algorithm for joint QoS and power optimization in mixed criticality 6G networks within a rate-splitting framework.

Findings

The algorithm achieves higher energy efficiency than comparative schemes.

There is a trade-off between QoS fulfillment and power minimization.

Energy efficiency gains are especially significant with mixed criticality users.

Abstract

Future sixth generation (6G) wireless communication networks face the need to similarly meet unprecedented quality of service (QoS) demands while also providing a larger energy efficiency (EE) to minimize their carbon footprint. Moreover, due to the diverseness of network participants, mixed criticality QoS levels are assigned to the users of such networks. In this work, with a focus on a cloud-radio access network (C-RAN), the fulfillment of desired QoS and minimized transmit power use is optimized jointly within a rate-splitting paradigm. Thereby, the optimization problem is non-convex. Hence, a low-complexity algorithm is proposed based on fractional programming. Numerical results validate that there is a trade-off between the QoS fulfillment and power minimization. Moreover, the energy efficiency of the proposed rate-splitting algorithm is larger than in comparative schemes, especially with mixed criticality.